Token Classification
Transformers
ONNX
Safetensors
modernbert
ner
on-device
privacy
flowx
openner
banking
de-identification
Instructions to use flowxai/kycextract with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use flowxai/kycextract with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="flowxai/kycextract")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("flowxai/kycextract") model = AutoModelForTokenClassification.from_pretrained("flowxai/kycextract", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from flowxai/kycextract: direct link, hf CLI and curl.
- Browser
- Download file 3.58 MB
-
https://huggingface.co/flowxai/kycextract/resolve/0bee9ca49d898c183a8465f1ee0f47084a6d2f9e/tokenizer.json
- Command line
-
hf download hf://flowxai/kycextract@0bee9ca49d898c183a8465f1ee0f47084a6d2f9e/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/flowxai/kycextract/resolve/0bee9ca49d898c183a8465f1ee0f47084a6d2f9e/tokenizer.json
3.58 MB
File too large to display, you can check the raw version instead.